Abstract: A method on a mobile device for voice recognition training is described. A voice training mode is entered. A voice training sample for a user of the mobile device is recorded. The voice training mode is interrupted to enter a noise indicator mode based on a sample background noise level for the voice training sample and a sample background noise type for the voice training sample. The voice training mode is returned to from the noise indicator mode when the user provides a continuation input that indicates a current background noise level meets an indicator threshold value.

Abstract: A system includes a fingerprint sensor, an application processor, and an auxiliary processor. The application processor is operable to arm the fingerprint sensor prior to the application processor entering a low power or sleep mode. The auxiliary processor is to receive a state output from the fingerprint sensor. The state output is to cause activation of one or more functions of the auxiliary processor upon fingerprint authentication while leaving the application processor in the low power or sleep mode.

Abstract: A method on a mobile device for voice recognition training is described. A voice training mode is entered. A voice training sample for a user of the mobile device is recorded. The voice training mode is interrupted to enter a noise indicator mode based on a sample background noise level for the voice training sample and a sample background noise type for the voice training sample. The voice training mode is returned to from the noise indicator mode when the user provides a continuation input that indicates a current background noise level meets an indicator threshold value.

Abstract: A method on a mobile device for voice recognition training is described. A voice training mode is entered. A voice training sample for a user of the mobile device is recorded. The voice training mode is interrupted to enter a noise indicator mode based on a sample background noise level for the voice training sample and a sample background noise type for the voice training sample. The voice training mode is returned to from the noise indicator mode when the user provides a continuation input that indicates a current background noise level meets an indicator threshold value.

Abstract: A system includes a fingerprint sensor, an application processor, and an auxiliary processor. The application processor is operable to arm the fingerprint sensor prior to the application processor entering a low power or sleep mode. The auxiliary processor is to receive a state output from the fingerprint sensor. The state output is to cause activation of one or more functions of the auxiliary processor upon fingerprint authentication while leaving the application processor in the low power or sleep mode.

Abstract: A method on a mobile device for voice recognition training is described. A voice training mode is entered. A voice training sample for a user of the mobile device is recorded. The voice training mode is interrupted to enter a noise indicator mode based on a sample background noise level for the voice training sample and a sample background noise type for the voice training sample. The voice training mode is returned to from the noise indicator mode when the user provides a continuation input that indicates a current background noise level meets an indicator threshold value.

Abstract: A system includes a fingerprint sensor, an application processor, and an auxiliary processor. The application processor is operable to arm the fingerprint sensor prior to the application processor entering a low power or sleep mode. The auxiliary processor is to receive a state output from the fingerprint sensor. The state output is to cause activation of one or more functions of the auxiliary processor upon fingerprint authentication while leaving the application processor in the low power or sleep mode.

Abstract: A method on a mobile device for voice recognition training is described. A voice training mode is entered. A voice training sample for a user of the mobile device is recorded. The voice training mode is interrupted to enter a noise indicator mode based on a sample background noise level for the voice training sample and a sample background noise type for the voice training sample. The voice training mode is returned to from the noise indicator mode when the user provides a continuation input that indicates a current background noise level meets an indicator threshold value.

Abstract: A method on a mobile device for voice recognition training is described. A voice training mode is entered. A voice training sample for a user of the mobile device is recorded. The voice training mode is interrupted to enter a noise indicator mode based on a sample background noise level for the voice training sample and a sample background noise type for the voice training sample. The voice training mode is returned to from the noise indicator mode when the user provides a continuation input that indicates a current background noise level meets an indicator threshold value.

Abstract: A method on a mobile device for voice recognition training is described. A voice training mode is entered. A voice training sample for a user of the mobile device is recorded. The voice training mode is interrupted to enter a noise indicator mode based on a sample background noise level for the voice training sample and a sample background noise type for the voice training sample. The voice training mode is returned to from the noise indicator mode when the user provides a continuation input that indicates a current background noise level meets an indicator threshold value.

Abstract: A method and system for voice recognition are disclosed. In one example embodiment, the method includes receiving voice input information by way of a receiver on a mobile device and performing, by way of at least one processing device on the mobile device, first and second processing operations respectively with respect to first and second voice input portions, respectively, which respectively correspond to and are based at least indirectly upon different respective portions of the voice input information. The first processing operation includes a speech-to-text operation and the second processing operation includes an alternate processing operation. Additionally, the method includes generating recognized voice information based at least indirectly upon results from the first and second processing operations, and performing at least one action based at least in part upon the recognized voice information, where the at least one action includes outputting at least one signal by an output device.

Abstract: A system includes a fingerprint sensor, an application processor, and an auxiliary processor. The application processor is operable to arm the fingerprint sensor prior to the application processor entering a low power or sleep mode. The auxiliary processor is to receive a state output from the fingerprint sensor. The state output is to cause activation of one or more functions of the auxiliary processor upon fingerprint authentication while leaving the application processor in the low power or sleep mode.

Abstract: A method on a mobile device for voice recognition training is described. A voice training mode is entered. A voice training sample for a user of the mobile device is recorded. The voice training mode is interrupted to enter a noise indicator mode based on a sample background noise level for the voice training sample and a sample background noise type for the voice training sample. The voice training mode is returned to from the noise indicator mode when the user provides a continuation input that indicates a current background noise level meets an indicator threshold value.

Abstract: A method and system for voice recognition are disclosed. In one example embodiment, the method includes receiving voice input information by way of a receiver on a mobile device and performing, by way of at least one processing device on the mobile device, first and second processing operations respectively with respect to first and second voice input portions, respectively, which respectively correspond to and are based at least indirectly upon different respective portions of the voice input information. The first processing operation includes a speech-to-text operation and the second processing operation includes an alternate processing operation. Additionally, the method includes generating recognized voice information based at least indirectly upon results from the first and second processing operations, and performing at least one action based at least in part upon the recognized voice information, where the at least one action includes outputting at least one signal by an output device.

Abstract: A communication device (100) includes a transceiver (115) for receiving a call, a received calls memory (145) for storing call sources (300) and for storing an associated call count (315) for each call source (310), a user preferences memory (140) for storing a set of call quantity categories and a corresponding set of alerts, and a processor (120). The processor (120) is programmed to: identify a call source of a received call, retrieve a call count for the call source, categorize the call count into a call quantity category, provide a command signal to an alert circuit (130) identifying a unique alert associated with the call quantity category, and optionally increment the call count. The communication device (100) further includes the alert circuit (130) for alerting using the unique alert identified by the processor (120).

Abstract: A communication device (100) includes a transceiver (115) for receiving a call, a received calls memory (145) for storing call sources (300) and for storing an associated call count (315) for each call source (310), and a processor (120). The processor (120) is programmed to: identify a call source of a received call, generate a command signal to an alert circuit (130) identify a unique alert associated with the call count, and increment the call count. The communication device (100) further includes the alert circuit (130) for alerting using the unique alert identified by the processor (120).